Self-learning automated techniques for detecting the usage of software packages

ABSTRACT

The systems and methods provided herein determine at least one first file system path related to a specific software package. A second file system path associated with a computing process running on the computer system is determined, and use of the specific software package on the computer system is detected based on comparing the first file system path with the second file system path. Thus, the present techniques determine the installation director(ies) of the application(s) and then compare active processes to determine whether an application is in use or is only installed.

CROSS REFERENCE TO RELATED APPLICATIONS

The following disclosure is based on and claims the benefit of andpriority under 35 U.S.C. § 120 to U.S. patent application Ser. No.16/021,852, filed Jun. 28, 2018, and the disclosure of which isincorporated in its entirety into the present continuation by reference.

BACKGROUND 1. Technical Field

Present invention embodiments relate to detecting the usage of asoftware package installed on a computer system, and more specifically,to automated self-learning techniques for detecting the usage ofsoftware packages.

2. Discussion of the Related Art

In software asset management, an administrator needs to know what typesof software are installed, and whether the installed software is beingused.

SUMMARY

According to embodiments of the present invention, self-learning andautomated techniques are provided for determining usage of anapplication installed on a system. Path information related to theinstallation directory/directories of the application may be used inthis determination.

The techniques comprise determining at least one first file system pathrelated to a specific software package and a second file system pathassociated with a computing process running on the computer system. Useof the specific software package on the computer system is detectedbased on comparing the first file system path with the second filesystem path. Thus, the present techniques determine the installationdirector(ies) of the application(s) and then compare active processes todetermine whether an application is in use or is only installed.

It is to be understood that the Summary is not intended to identify keyor essential features of embodiments of the present disclosure, nor isit intended to be used to limit the scope of the present disclosure.Other features of the present disclosure will become easilycomprehensible through the description below.

BRIEF DESCRIPTION OF THE DRAWINGS

Generally, like reference numerals in the various figures are utilizedto designate like components. Through the more detailed description ofsome embodiments of the present disclosure in the accompanying drawings,the above and other features and advantages of the present disclosurewill become more apparent.

FIG. 1 is a block diagram of an example computing environment forself-learning and automated detection of software package usage inaccordance with embodiments of the present disclosure.

FIG. 2 is a detailed flowchart of operations for self-learning andautomated detection of software package usage using software catalogs ortags, according to embodiments of the present disclosure.

FIG. 3 is a high level flowchart of operations for self-learning andautomated detection of software package usage, according to embodimentsof the present disclosure.

DETAILED DESCRIPTION

An example environment 100 for use with present invention embodiments isillustrated in FIG. 1. Specifically, the environment includes one ormore server systems 10, and one or more client or end-user systems 20.Server systems 10 and client systems 20 may be remote from each otherand communicate over a network 35. The network may be implemented by anynumber of any suitable communications media (e.g., wide area network(WAN), local area network (LAN), Internet, Intranet, etc.).Alternatively, server systems 10 and client systems 20 may be local toeach other, and communicate via any appropriate local communicationmedium (e.g., local area network (LAN), hardwire, wireless link,Intranet, etc.).

Client systems 20 enable users to view the results generated by serversystem 10. The server systems 10 may include a self-learning module 15to automatically determine which software packages are being utilized,as described in additional detail below. Although a client serverrelationship is shown in FIG. 1, it is understood that otherconfigurations are possible. For example, in an enterprise system,self-learning module 15 may be present on each endpoint. The results foreach endpoint are then provided to a server system 10 for compilationand analysis.

A database system 30 may store various information for the analysis(e.g., a usage fact repository 32, an unmatched software packagerepository 34, a software catalog 36, matched software packagerepository 38, etc.). The database system may be implemented by anyconventional or other database or storage unit, may be local to orremote from server systems 10 and client systems 20, and may communicatevia any appropriate communication medium (e.g., local area network(LAN), wide area network (WAN), Internet, hardwire, wireless link,Intranet, etc.). The client systems may present a graphical user (e.g.,GUI, etc.) or other interface 28 (e.g., command line prompts, menuscreens, etc.) to solicit information from users pertaining to thedesired software package usage and analysis, and may provide reportsincluding various analysis results (e.g., software package usageanalytics, software package version information, location ofinstallation, duplicate software packages, unmatched software packages,system wide or enterprise usage statistics, etc.).

Usage fact repository 32 may contain a list of usage facts comprisingactive processes and corresponding file paths (location) of theexecutable file that generates the active process. In some aspects, thisinformation may be compiled over different periods of time, to indicatewhich processes are active in certain time windows. Unmatched softwarepackage repository 34 may comprise a list of unmatched active processesand may provide this to signature analysis module 125 for furtheranalysis. A software catalog 36 may include a listing of installationpaths for installed software packages. This may be updated by module130, and as unmatched processes are identified, these are added to thesoftware catalog. Additionally, module 130 may extract path informationfrom the software catalog which is provided to path matching module 115for analysis. Matched software package repository 38 may comprise a listof matched active processes.

Server systems 10 and client systems 20 may be implemented by anyconventional or other computer systems preferably equipped with adisplay or monitor, a base (e.g., including at least one processor 16,22, one or more memories 17, 24 and/or internal or external networkinterfaces or communications devices 18, 26 (e.g., modem, network cards,etc.)), optional input devices (e.g., a keyboard, mouse or other inputdevice), user interface 19, 28, and any commercially available andcustom software (e.g., server/client communications software,self-learning module 15, etc.).

Alternatively, one or more client systems 20 may detect the usage ofsoftware packages when operating as a stand-alone unit. In a stand-alonemode of operation, the client system stores or has access to the data(e.g., software catalogs, etc.), and includes self-learning module 15 todetermine file paths of installed applications as well as file pathsassociated with actively running processes. The client system maycompare the normalized file paths corresponding to the installedsoftware package to the usage facts corresponding to the activelyrunning processes to determine whether there is a match, e.g., a usagefact directory path falling within a subdirectory of the normalized filepath. The graphical user (e.g., GUI, etc.) or other interface (e.g.,command line prompts, menu screens, etc.) solicits information from acorresponding user pertaining to the desired analysis, and may providereports including analysis results.

Self-learning module 15 may include one or more modules or units toperform the various functions of present invention embodiments describedherein. The various modules (e.g., software detection and monitoringmodule 105, path normalization module 110, path matching module 115,unmatched process module 120, signature analysis module 125, softwarecatalog extraction and modification module 130, etc.) may be implementedby any combination of any quantity of software and/or hardware modulesor units, and may reside within memories 17, 24 of the server and/orclient systems for execution by processors 16, 22.

In some embodiments, the present techniques and systems are compatiblewith ISO 19770-2 enabled products which utilizes an ISO SWID standardfor tagging software. For example, ISO SWID may act as an identificationtag for a software package. The ISO SWID indicates the installationdirectory for a software package, and this installation directory may becompared against active processes running from thedirectory/subdirectories. Thus, using identification tags, softwarepackages may be identified locally, on the system in which such packagesare installed.

In general, the SWID tag comprises a structured metadata format fordescribing a software product, which may include the software productname, the product version, file extension, the organization which ownsthe product, the content of the software product, the relationships toother software products, and other descriptive information about thesoftware product's lifecycle. In some aspects, a file may have a fileextension that ends in “.swidtag”.

Software detection and monitoring module 105 comprises functionality to:(1) detect software installation paths (e.g., based on a softwarecatalog or a SWID tag), and to (2) monitor active processes to generatea usage fact repository 32 that may include usage statistics pertainingto the detected software packages. This information may be analyzed, inan automated and self-learning manner to determine the usage of thesoftware package based on the operations of FIGS. 2-3.

Path normalization module 110 normalizes the software installationpaths. Module 110 may identify the root or top-level directory of theinstalled application, and may normalize the path such that thetop-level directory is maintained and subdirectories are removed. TheISO standard specifies that the installation of software follow thepattern /opt/abc/lmt/iso-swid, wherein iso-swid is a subdirectorycorresponding to the particular application being installed.

Path matching module 115 compares active application file paths tosoftware installation paths, which may be normalized by module 110.Normalization allows the system to match all possible versions of theapplication, and to self-learn new versions of the applications.

Unmatched process module 120 identifies active processes that were notmatched by path matching module 115. This module may pass a list of theunmatched processes to signature analysis module 125 for furtheranalysis.

Signature analysis module 125 may be used to identify unmatched activeprocesses. This module may compare a name of the active process (or anyother suitable active process information) to identify the unmatchedactive process, e.g., by comparing to a usage signature catalog.Signature analysis module may also normalize the unmatched activeprocesses to facilitate comparison. In some cases, a match may bepositive provided that there is sufficient similarity between the termsbeing compared, e.g., the terms do not have to match exactly, but shouldbe similar or have some other feature to identify the active process.

Software catalog extraction and modification module 130 may maintain alist of installation paths corresponding to active processes. Forprocesses involving SWID tags, the software catalog extraction modulemay not be needed, however, for catalog based processes, this module maygenerate and maintain a list of active processes and correspondinginstallation paths for future analysis. Once the installation file pathis identified, this information along with the active process name maybe provided to module 130 for inclusion into the software catalog.Module 130 may also extract file paths from the software catalog 36,which are used to compare file paths of active processes withinstallation paths.

FIG. 2 shows example operations performed by the modules listed above.With reference to software detection and monitoring module 105, atoperation 205, active software processes are detected to determine usagefacts. The system may monitor actively running processes on a computer,and for each active process, may extract the file path corresponding tothe active process. In some cases, the system may identify whichprocesses are part of the operating system of the computer, and mayexclude these from the analysis, as these processes are fundamental tothe operation of the system, and will generally be active whenever thecomputer is operating. In other cases, the system may evaluate allactive processes.

The system may detect new active processes at periodic intervals or asthese processes are launched, e.g., by another program or a user. Thesystem may store a list of active processes as these processes aredetected, and from a subsequent scan, may identify which processes arenewly active (e.g., from a user or other process launching a newprocess) or no longer active (no longer detectable). The system mayinterface with a module (e.g., custom developed or part of the operatingsystem, in some cases, similar to a task manager) that monitors activeprocesses to obtain such information.

In some cases, a usage fact may correspond to a directory path(including the name of the active software package) with usagestatistics. At operation 210, file paths are detected, using the ISOSWID tag (or any other suitable equivalent) or using a software catalog.For example, based on the ISO standard, SWID files may end in afile-specific extension (e.g., “.swidtag”) to allow ease ofidentification of SWID tag files and the corresponding directory or filepath in which the SWID tag is located. The SWID tag file may have alocation of /opt/abc/lmt/iso-swid/filename.swidtag, which may yield thedirectory or file path /opt/abc/lmt/iso-swid/. This information may beprovided as inputs to other modules.

With reference to path normalization module 110, and at operation 215,each detected directory path or file path from operation 210 may benormalized (e.g., to the root directory with regard to installation ofthe software package). For example, /opt/abc/lmt/iso-swid may benormalized to /opt/abc/lmt/. This module removes subdirectories so thatthe root or top level of the program installation directory isgenerated.

With reference to path matching module 115, and at operation 220, foreach detected usage fact corresponding to an active process, the usagefact may be compared with the normalized detected directory path todetermine if the usage fact (in particular, the file path for an activesoftware package or program) is within (matches) the normalized detecteddirectory path. The normalized detected directory path contains theinstallation path of the software package as determined by the SWID tagor software catalog. For example, a usage fact comprising theinstallation path of a binary file /opt/abc/lmt/bin/lmt.bin may becompared to the normalized detected directory path from operation 215,which is /opt/abc/lmt/. Here, the path /opt/abc/lmt/bin/lmt.bin iswithin a subdirectory of /opt/abc/lmt and a comparison between these twopaths leads to a match. As another example, the path/var/opt/abc/lmt/lmt.bin is within /var/opt/abc/lmt, and a comparisonbetween these two paths leads to a match.

Thus, the system has the capability to identify and extract orself-learn newly installed software packages based on identifying a tagassociated with the installed software package, and extracting the filepath corresponding to the location of the tag. In some cases, the tag isdetectable or recognizable by the system at the file directory level(e.g., a particular file type extension, e.g., such as .swidtag). Inother cases, all files within a specified directory of a file system areindicative of installed software, and all such files are considered. Instill other cases, the system may scan file type extensions in order toidentify files associated with running processes (e.g., .bin, .exe,etc.); in some cases, the system may scan files up to a certain depth ofthe directory (e.g., within 4 or 5 subdirectories deep) so as not toscan the entire system.

In some aspects, installation paths may be obtained using, e.g., SQLqueries Usage_fact.path such as “path %” or by identifying theinstallation path defined inside the ISO SWID file for a given softwarepackage.

At operation 225, if there are multiple active software packages, theprocess repeats at operation 205, until all active software packageshave been analyzed according to this process.

At operation 230 and also with regard to the path matching module 115,for usage facts matching multiple directory paths (e.g., cases in whichthe same process is used by two different software packages), the bestmatch may be selected. In some cases, the longest installation path isselected as the best match. For example, Java may be running as aJava.exe process both as a primary software and as an embedded software,e.g., by a program that runs using Java. In some cases, it may bedesirable to correlate Java usage with the embedded Java component andnot with the primary Java installed product. For example, in some cases,the longer installation path may correlate with the embedded Javacomponent and the shorter installation path may correlate with theprimary Java component. Without installation path information, it is notpossible to discern which Java process correlates with which process(e.g., primary or embedded). In cases in which multiple installationpaths have the same length and refer to the same installation directory,all matches are generally kept.

With reference to unmatched process module 120, and at operation 235,unmatched usage facts (processes not matching a normalized directorypath) may be processed through behavioral signature matching. Unmatchedprocesses include active software packages without a correspondinginstallation path, incomplete or out of date catalog entries that nolonger correspond to newer or upgraded software packages, cases in whichSWID tags for different processes are placed in a common location, otheractive processes not installed according to ISO standards, etc.Likewise, detected normalized directories or detected directories thatdo not have a corresponding process match, may indicate that thesoftware package is not active. Behavioral signature matching involvestechniques to match based on similarity and therefore matches may not beexact.

Signature analysis module 125 may also normalize signature matches forusage facts that are matched with multiple software names. For example,signature analysis module may also perform normalization and/orfiltering operations, including excluding software processes matchedwith a file path, excluding software reporting unique path if still morethan one match, and keeping the remaining matches.

In some aspects, the signature analysis module 125 may use a softwarecatalog with predefined usage signatures as well as custom signaturescreated by users to perform behavioral signature matching. If only oneinstance of a software process is discovered on a given endpoint, pathinformation may be ignored. In general, signature analysis module 125may identify processes that are not run from the directory in which thecorresponding software package is installed. Thus, behavioral signaturematching using this module may not be possible when software isinstalled in many locations.

As an example, software A is matched through path based matching toprocess P1 and is additionally matched by usage signature to process P2.Software B is matched by usage signature to process P2, which is thesame as software A. In this case, process P2 is assigned only tosoftware B as software A has already assigned process P1.

As another example, software A is matched through path based matching toprocess P1, and software B is matched through path based matching toprocess P1. In this case, process P1 is assigned to both software A andsoftware B.

In yet another example, process P1 is executed from DIR_P1 /opt/dir_p1/and is not matched using path based matching. Software A is installed indirectory DIR_A /opt/dir_a/ and has a usage signature named process P1.Therefore, process P1 is matched by signature to software A.

For operation 240 and with regard to software catalog extraction andmodification module, unmatched usage facts that have been identified bymodule 125 may be added to the software catalog. Alternatively, thismodule may also extract files paths from a software catalog and mayprovide the extracted file paths to the path matching modules 115 forfurther analysis.

FIG. 3 shows high level operations of detecting active software packagesthat have been installed. At operation 310, at least one first filesystem path related to a specific software package is determined. Atoperation 320, a second file system path associated with an activecomputing process running on the computer system is determined. Atoperation 330, the specific software package is detected to be used onthe computer system based on comparing the first file system path withthe second file system path.

Methods and systems are provided herein, which provide a way to identifynew software installations in an automated manner, and to identify whichinstallations are active. Further, the techniques are adaptable tochanging software names and versions, as the techniques may self-learninstalled software package names in an automated manner.

These techniques can be extended across enterprise systems to makedecisions regarding software installation and to better utilize softwareresources. In an enterprise setting, the present techniques may be usedto gather software package usage information from all monitoredendpoints. This usage information may be stored in a centralizedlocation and analyzed to determine usage of installed software. Thetechniques may be rerun on a periodic basis in order to account forchanges in the network (e.g., addition or removal of new endpoints),software upgrades on an endpoint, software removal on an endpoint, filepath changes on an endpoint, etc. Accordingly, any of the aforementionedchanges may be made, and the present techniques may be used to gatherthe updated information in an automated, self-learning manner.

The approaches described herein have several advantages. For example,applications not installed in a common directory may be detected usingsoftware identification tags. Additionally, identification of softwarepackages is not limited to those that are visible on the system list ofactive software processes. Further, for unmatched software processes,the present approaches may use a custom software catalog, which mayinclude user defined entries to identify software processes, and istypically stored locally to the computer on which the software processesare active.

In some aspects, the techniques may also be applied to system registriesor as part of a deep file system analysis (e.g., traversing through alarge number of nested subdirectories to analyze more locations withinthe computer system) to obtain file path information of installedsoftware packages. Parsing through the registry may provide informationabout installation directories or individual files.

In some aspects, when the system determines that an installed file isnot active, the system may record in a database that the file is notactive. Whether at periodic intervals or based on detecting a new activeprocess (e.g., a user or other process launching a new file), the systemmay determine that the file has not been active for an interval of timedefined by a user (e.g., a week, one month, three months, one year). Insome embodiments, the system may automatically remove or uninstall thesoftware package from the system, e.g., to free up a license for anotheruser in an enterprise environment or to free up resources on a computer.In other cases, the system may provide a notification to a networkadministrator regarding manual uninstallation of the software. In stillother cases, if a shared license among a group of users is being heavilyutilized, the system may send a notification to the networkadministrator regarding high usage of the software, e.g., to indicatethat additional licenses are needed to optimize productivity.

In other aspects, the active process list and arguments passed to thesoftware which generated the active process list may be captured andexamined.

It will be appreciated that the embodiments described above andillustrated in the drawings represent only a few of the many ways ofimplementing embodiments for automatically determining usage of softwarepackages in a self-learning manner.

The environment of the present invention embodiments may include anynumber of computer or other processing systems (e.g., client or end-usersystems, server systems, etc.) and databases or other repositoriesarranged in any desired fashion, where the present invention embodimentsmay be applied to any desired type of computing environment (e.g., cloudcomputing, client-server, network computing, mainframe, stand-alonesystems, etc.). The computer or other processing systems employed by thepresent invention embodiments may be implemented by any number of anypersonal or other type of computer or processing system (e.g., desktop,laptop, PDA, mobile devices, etc.), and may include any commerciallyavailable operating system and any combination of commercially availableand custom software (e.g., communications software, server software,self-learning module, client software, etc.). These systems may includeany types of monitors and input devices (e.g., keyboard, mouse, voicerecognition, etc.) to enter and/or view information.

It is to be understood that the software (e.g., self-learning module 15,including software detection and monitoring module 105, pathnormalization module 110, path matching module 115, unmatched processmodule 120, and signature analysis module 125, software catalogextraction and modification module 130, etc.) of the present inventionembodiments may be implemented in any desired computer language andcould be developed by one of ordinary skill in the computer arts basedon the functional descriptions contained in the specification and flowcharts illustrated in the drawings. Further, any references herein ofsoftware performing various functions generally refer to computersystems or processors performing those functions under software control.The computer systems of the present invention embodiments mayalternatively be implemented by any type of hardware and/or otherprocessing circuitry.

The various functions of the computer or other processing systems may bedistributed in any manner among any number of software and/or hardwaremodules or units, processing or computer systems and/or circuitry, wherethe computer or processing systems may be disposed locally or remotelyof each other and communicate via any suitable communications medium(e.g., LAN, WAN, Intranet, Internet, hardwire, modem connection,wireless, etc.). For example, the functions of the present inventionembodiments may be distributed in any manner among the variousend-user/client and server systems, and/or any other intermediaryprocessing devices. The software and/or algorithms described above andillustrated in the flow charts may be modified in any manner thataccomplishes the functions described herein. In addition, the functionsin the flow charts or description may be performed in any order thataccomplishes a desired operation.

The software of the present invention embodiments (e.g., self-learningmodule 15, including software detection and monitoring module 105, pathnormalization module 110, path matching module 115, unmatched processmodule 120, and signature analysis module 125, software catalogextraction and modification module 130, etc.) may be available on anon-transitory computer useable medium (e.g., magnetic or opticalmediums, magneto-optic mediums, floppy diskettes, CD-ROM, DVD, memorydevices, etc.) of a stationary or portable program product apparatus ordevice for use with stand-alone systems or systems connected by anetwork or other communications medium.

The communication network may be implemented by any number of any typeof communications network (e.g., LAN, WAN, Internet, Intranet, VPN,etc.). The computer or other processing systems of the present inventionembodiments may include any conventional or other communications devicesto communicate over the network via any conventional or other protocols.The computer or other processing systems may utilize any type ofconnection (e.g., wired, wireless, etc.) for access to the network.Local communication media may be implemented by any suitablecommunication media (e.g., local area network (LAN), hardwire, wirelesslink, Intranet, etc.).

The system may employ any number of any conventional or other databases,data stores or storage structures (e.g., files, databases, datastructures, data or other repositories, etc.) to store information(e.g., usage fact repository 32, unmatched software package repository34, software catalog 36, matched software package repository 38, etc.).The database system may be implemented by any number of any conventionalor other databases, data stores or storage structures (e.g., files,databases, data structures, data or other repositories, etc.) to storeinformation (e.g., usage fact repository 32, unmatched software packagerepository 34, software catalog 36, matched software package repository38, etc.). The database system may be included within or coupled to theserver and/or client systems. The database systems and/or storagestructures may be remote from or local to the computer or otherprocessing systems, and may store any desired data (e.g., usage factrepository 32, unmatched software package repository 34, softwarecatalog 36, matched software package repository 38, etc.).

The present invention embodiments may employ any number of any type ofuser interface (e.g., Graphical User Interface (GUI), command-line,prompt, etc.) for obtaining or providing information (e.g., usage factrepository 32, unmatched software package repository 34, softwarecatalog 36, matched software package repository 38, etc.), where theinterface may include any information arranged in any fashion. Theinterface may include any number of any types of input or actuationmechanisms (e.g., buttons, icons, fields, boxes, links, etc.) disposedat any locations to enter/display information and initiate desiredactions via any suitable input devices (e.g., mouse, keyboard, etc.).The interface screens may include any suitable actuators (e.g., links,tabs, etc.) to navigate between the screens in any fashion.

The report may include any information arranged in any fashion, and maybe configurable based on rules or other criteria to provide desiredinformation to a user (e.g., enterprise usage analytics, usage at anendpoint, matched software packages, unmatched software packages, etc.).

The present invention embodiments are not limited to the specific tasksor algorithms described above, but may be utilized for any applicationin which a file specific tag can be used to derive file path informationwhich is them compared to file path information for active processes.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”,“comprising”, “includes”, “including”, “has”, “have”, “having”, “with”and the like, when used in this specification, specify the presence ofstated features, integers, steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, integers, steps, operations, elements, components,and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present invention has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Theembodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

What is claimed is:
 1. A method for detecting a usage of a softwarepackage installed on a computer system, the method comprising:determining at least one first file system path related to a specificsoftware package; determining a second file system path associated witha computing process actively running on the computer system; anddetecting that the specific software package is used on the computersystem based on comparing the first file system path with the secondfile system path.
 2. The method of claim 1, wherein the first filesystem path is extracted from a software catalog database, the softwarecatalog database describing a predefined set of software packages. 3.The method of claim 1, wherein the second file system path is a processdirectory and the first file system path is a root level directory, andwherein the second file system path has at least one subdirectory withinthe first file system path.
 4. The method of claim 1, furthercomprising: detecting a software identification tag file within a filesystem of the computer system; and determining the first file systempath based on a file system path where the software identification tagfile is located.
 5. The method of claim 4, further comprising:determining an identifier of the software package based on content ofthe software tag identification file, and storing the first file systempath into the software catalog database together with a calculatedidentifier of the software package.
 6. The method of claim 1, whereinthe method comprises: determining that a further computing processrunning on the computer system cannot be detected by comparing a thirdfile system path associated with the further computing process and theat least one first file system path with each other, and identifying asoftware package used on the computer system based on behavioralsignature matching.
 7. The method of claim 1, wherein the first filesystem path related to a specific software package is normalized suchthat subdirectories specific to the software package installation areremoved from the first file system path and a top-level-directory of thefirst file system path is maintained.
 8. The method of claim 1, whereincomparing the first file system path with the second file system pathreturns multiple matches, indicating that the software package is activeas a primary program and as an embedded program; and resolving whichactive process refers to the primary program and which active processrefers to the embedded program based on the length of the match.
 9. Acomputer system for detecting a usage of a software package installed ona computer system comprising at least one processor configured to:determine at least one first file system path related to a specificsoftware package; determine a second file system path associated with acomputing process actively running on the computer system; and detectthat the specific software package used on the computer system is basedon comparing the first file system path with the second file systempath.
 10. The system of claim 9, wherein the first file system path isextracted from a software catalog database, and the software catalogdatabase describes a predefined set of software packages.
 11. The systemof claim 9, wherein the second file system path is a process directoryand the first file system path is a root level directory, and whereinthe second file system path has at least one subdirectory within thefirst file system path.
 12. The system of claim 9, wherein the at leastone processor is further configured to: detect a software identificationtag file within a file system of the computer system; and determine thefirst file system path based on a file system path where the softwareidentification tag file is located.
 13. The system of claim 12, whereinthe at least one processor is further configured to: determine anidentifier of the software package based on content of the software tagidentification file, and store the first file system path into thesoftware catalog database together with a calculated identifier of thesoftware package.
 14. The system of claim 9, wherein the at least oneprocessor is further configured to: determine that a further computingprocess running on the computer system cannot be detected by comparing athird file system path associated with the further computing process andthe at least one first file system path with each other, and identify asoftware package used on the computer system based on behavioralsignature matching.
 15. The system of claim 9, wherein the first filesystem path related to a specific software package is normalized suchthat subdirectories specific to the software package installation areremoved from the first file system path and a top-level-directory of thefirst file system path is maintained.
 16. The system of claim 9, whereincomparing the first file system path with the second file system pathreturns multiple matches, indicating that the software package is activeas a primary program and as an embedded program, and wherein theprocessor is further configured to resolve which active process refersto the primary program and which active process refers to the embeddedprogram based on the length of the match.
 17. A computer program productfor detecting a usage of a software package installed on a computersystem, the computer program product comprising a computer readablestorage medium having program instructions embodied therewith, theprogram instructions executable by a processor to: determine at leastone first file system path related to a specific software package;determine a second file system path associated with a computing processactively running on the computer system; and detect that the specificsoftware package used on the computer system is based on comparing thefirst file system path with the second file system path.
 18. Thecomputer program product of claim 17, wherein the first file system pathis extracted from a software catalog database, and the software catalogdatabase describes a predefined set of software packages.
 19. Thecomputer program product of claim 17, wherein the second file systempath is a process directory and the first file system path is a rootlevel directory, and wherein the second file system path has at leastone subdirectory within the first file system path.
 20. The computerprogram product of claim 17, wherein the program instructions areexecutable to: detect a software identification tag file within a filesystem of the computer system; and determine the first file system pathbased on a file system path where the software identification tag fileis located.